Factor product utilization and health outcomes in patients with haemophilia A and B on extended half‐life concentrates: A Canadian observational study of real‐world outcomes
Bibliographic record
Abstract
INTRODUCTION: Recombinant factors VIII and IX Fc (rFVIIIFc/rFIXFc) became available in Canada in 2016 and were the only extended half-life (EHL) factor concentrates available in Canada until 2018. OBJECTIVES: We aim to describe the change in product utilization in Canadians who switched to rFVIIIFc/rFIXFc. METHODS: This prospective and retrospective cohort study enrolled males aged ≥6 years with moderate or severe haemophilia who switched to rFVIIIFc/rFIXFc and those who remained on standard half-life (SHL) between 2016 and 2018. Factor utilization and annualized bleeding rates (ABR) were collected at baseline, 1-year and 2-years. Due to low prospective enrolment (n = 25 switchers), prospective and retrospective data were pooled. RESULTS: 125 switchers (93 rFVIIIFc, 32 rFIXFc) and 33 non-switchers were included. The median age was 17 (rFVIIIFc) and 38 years (rFIXFc). Prior to switch, over 80% were on prophylaxis. There was a statistically significant reduction in the prescribed weekly prophylactic dose after the switch to rFVIIIFc/rFIXFc for all age groups, with a corresponding reduction (15-16%) in actual annualized FIX utilization in switchers (combined adults and children) to rFIXFc, and a smaller non-significant reduction in actual annualized FVIIII utilization (7%) in children who switched to rFVIIIFc. A significant reduction in the median ABR was only observed in children who switched to rFVIIIFc, but not in adults who switched to rFVIIIFc or rFIXFc. CONCLUSION: Switching from SHL to EHL products led to a small reduction in factor utilization, while preserving a low ABR in children and adults with haemophilia. Further patient-reported outcomes data will further elucidate the role of EHL in the haemophilia landscape.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".